Zur Seitenansicht


Data mining for the social sciences : an introduction / Paul Attewell and David B. Monaghan with Darren Kwong
VerfasserAttewell, Paul In der Gemeinsamen Normdatei der DNB nachschlagen In Wikipedia suchen nach Paul Attewell ; Monaghan, David B. In der Gemeinsamen Normdatei der DNB nachschlagen In Wikipedia suchen nach David B. Monaghan
ErschienenOakland, Calif. : Univ. of California Press, 2015
First ed.
UmfangXI, 252 S. : Ill., graph. Darst.
Includes bibliographical references and index
SchlagwörterSozialwissenschaften In Wikipedia suchen nach Sozialwissenschaften / Data Mining In Wikipedia suchen nach Data Mining
Download Data mining for the social sciences [0,26 mb]
Verfügbarkeit In meiner Bibliothek

"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"...Provided by publisher